Abstract:Carbon dioxide is produced by fossil energy consumption, and the growth of carbon dioxide emissions contributes to climate change,so the Beijing-Tianjin-Hebei zone energy consumption is under carbon dioxide emissions constrain. Firstly, all driving factors (such as gross domestic product (GDP) , population, urbanization rate, industrial mixture, energy consumption intensity) were predicted by classical time series models. And these prediction values were substituted into artificial neural network (ANN) as Independent input variables, the energy consumption as the output variable, and then all total energy consumption were respectively predicted in the Beijing-Tianjin-Hebei region. And their carbon dioxide emissions calculated by emission factor method was regarded as the constrain, then coal, oil, natural gas, other energy consumption were optimized by increase principle, the optimization results were the Beijing-Tianjin-Hebei region energy consumption pathway for climate change . The research results show: economy and society are dominating driving factors for energy consumption growth, the coal and oil energy consumption control is a core measure for the pathway of energy consumption under the carbon dioxide emissions constrain , the supply of natural gas and electricity is the key of energy consumption structure optimization.